1. Field of the Invention
The present invention generally relates to receivers in MIMO multiplexing communication system and signal separation methods, and especially relates to such a receiver and method employing LSD (List Sphere Decoding) method with adaptive selection of surviving symbol replica candidates.
2. Description of the Related Art
MIMO (Multiple Input Multiple Output) spatial multiplexing is one technology to realize large capacity and high speed data communications. FIG. 1 schematically illustrates a general structure of a MIMO multiplexing system 10. In the MIMO multiplexing system 10, a transmitter 100 transmits plural different signals or data via plural different antenna branches 101, 102, . . . , using the same frequency, time and/or code. A receiver 200 receives spatially multiplexed plural different signals via antennas 201, 202, . . . , and separates the received signals to retrieve the transmitted signals or data. Since the MIMO multiplexing system can transmit and receive different data simultaneously, it can drastically increase information bit rate.
Some signal separation schemes have been proposed for the MIMO multiplexing. Among them, the maximum likelihood of detection (MLD) method is desirable, because the MLD method has excellent signal separation characteristics, and can reduce a required signal energy per bit-to-noise power spectrum density ratio (Eb/No) and therefore realize high throughput. In the MLD method, however, it is necessary to calculate the branch metrics (squared Euclidean distances) of all possible symbol replica candidates with respect to all the transmission branches (transmitted signals), and therefore the calculation amount and complexity is extremely large. In the MLD, the transmitted signals can be retrieved on the assumption that a combination of symbol replica candidates giving the minimum branch metrics is the correct combination of the transmitted signals. It is desired to reduce the calculation amount and complexity for the actual implementation of the MLD method.
As one promising approach that reduces the calculation amount in the MLD method, the List Sphere Decoding (LSD) method has been proposed. In the LSD method, the QR decomposition technique is used to orthogonalize the transmitted signals (into a condition where each received signal includes only a specific transmitted signal component(s) but not other transmitted signal components, as shown in FIG. 2). A suitable threshold is previously established. The transmitted signals or transmission branches are sorted or ranked in the decreasing order of their received SINRs (Signal to Interference plus Noise power Ratios). The branch metrics of symbol replica candidates with respect to the transmission branches are compared with the threshold, in the decreasing order of their received SINRs. In accordance with a result of the comparison, the symbol replica candidates with respect to the lower ranked transmitted signals (See Non-Patent Document #1) are deleted.
The QR decomposition is described below in more detail. Assuming that the transmitted signals are represented by x (x1, x2, x3 and x4 where four transmission antenna branches are used) and the received signals are represented by y (y1, y2, y3 and y4 where four receiving antennas are used), the received signals can be represented by the following equation (1).y=Hx  (1)
H is a channel matrix that can be obtained by performing channel estimation in the receiver using known orthogonal pilot signals multiplexed with the transmission signals. The orthogonal pilot signals are multiplexed to the transmitted signal by any of or a combination of time division multiplexing, frequency division multiplexing, and code division multiplexing.
A unitary matrix Q and an upper triangular matrix R satisfying the following equation (2) are determined.H=QR  (2)
The above equation (1) can be represented by the following equation (3) using QR.y=Hx=QRx  (3)
The Hermitian transposed matrix QH of the matrix Q is multiplied to both sides of the equation (3) from the left to get the following equation (4).QHy=QHQRx=Rx  (4)
An equation shown in FIG. 2 indicates the components x1, x2, x3 and x4 of the transmitted signals x and the components z1, z2, z3 and z4 of the received signals QHy obtained by orthogonalizing the transmitted signals x. For example, since the component z1=r44x1, it includes only the component x1 but not other components of x. The component z2 includes only the components x1 and x2. This condition is referred to as “orthogonal” herein.
As for the received signals z by thus orthogonalizing the transmitted signals x using the upper triangular matrix R, the branch metric with respect to each symbol replica candidate (S1, S2, S3, S4, S5, S6, . . . ) for each transmitted signal (x1, x2, x3, x4) transmitted at the antenna branch 101 is compared with the threshold by turns. In accordance with the comparison result (e.g. a solid line white circle S1 for x1 at stage 1 shown in FIG. 3 is larger than the threshold), lower ranked symbol replica candidates (e.g. the following symbol replica candidates represented by four dotted line white circles at stage 2) for the transmitted signals (e.g. x2 at stage 2 shown in FIG. 3) are deleted to reduce the calculation amount. Each stage corresponds to each transmitting antenna branch, therefore to each transmitted signal. By deciding symbol replica candidates at each stage, the transmitted signal is retrieved at each antenna branch.
FIG. 3 schematically illustrates the branch metric calculation and comparison procedure of the above described LSD method under a condition where the QPSK (Quadrature Phase Shift Keying) modulation and 2×2 MIMO multiplexing are employed. Solid and dotted line white circles represent symbol replica candidates that have been deleted according to the comparison with the threshold. Black circles represent surviving symbol replica candidates. In this example, the calculation and comparison procedure starts at step S1, goes through steps S2, S3, S4, S5, S6, S7, S8, S9, S10 and S13, and ends at step S12.
[Non-patent Document #1]
B. M. Hochwald, et al., “Achieving near-capacity on multiple-antenna channel,” IEEE Trans. Commun., vol. 51, no. 3, pp. 389-399, March 2003.